Sonda Bousnina

Papers

Total Citations

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About

Sonda Bousnina is a researcher whose work lies at the intersection of computer vision and mobile robotics, with a particular focus on visual detection and tracking systems. Her most cited paper, "Learning system for mobile robot detection and tracking" (2012, 13 citations), addresses the challenging problem of enabling robots to perceive and follow targets in dynamic environments. In this work, she introduced a target-tracking system that leverages Gabor filters to extract distinctive robot features, contributing to more robust and reliable autonomous navigation. While her citation count reflects a focused and emerging impact, Bousnina’s research is foundational for applications in surveillance, human-robot interaction, and autonomous exploration. Her work underscores the importance of feature extraction in real-time tracking, a critical component for advancing mobile robot autonomy. As a researcher, she bridges theoretical computer vision techniques with practical robotic implementations, offering valuable insights for students and engineers developing intelligent, perception-driven systems.